[PRE REVIEW]: PANINIpy: Package of Algorithms for Nonparametric Inference with Networks in Python

[editorialbot]

Submitting author: @baiyueh (Baiyue He)
Repository: https://github.com/baiyueh/PANINIpy
Branch with paper.md (empty if default branch):
Version: v1.0
Editor: @vissarion
Reviewers: @ankurankan, @gchure
Managing EiC: Chris Vernon

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[editorialbot]

Software report:

github.com/AlDanial/cloc v 1.90  T=0.74 s (71.4 files/s, 688212.9 lines/s)
-------------------------------------------------------------------------------
Language                     files          blank        comment           code
-------------------------------------------------------------------------------
CSV                              7              0              0         503219
Python                          14            298            342           1169
reStructuredText                13           1221           2882            586
Jupyter Notebook                 4              0            348            211
Markdown                         8             89              0            164
TeX                              1             13              0            143
CSS                              1             12              0             55
YAML                             2              6             22             38
DOS Batch                        1              8              1             26
make                             1              4              7              9
HTML                             1              1              0              5
-------------------------------------------------------------------------------
SUM:                            53           1652           3602         505625
-------------------------------------------------------------------------------

Commit count by author:

    57	Baiyue
    21	Alec Kirkley
     9	baiyueh

[editorialbot]

Paper file info:

📄 Wordcount for paper.md is 1061

✅ The paper includes a Statement of need section

[editorialbot]

License info:

✅ License found: MIT License (Valid open source OSI approved license)

[editorialbot]

Reference check summary (note 'MISSING' DOIs are suggestions that need verification):

✅ OK DOIs

- 10.6084/m9.figshare.1164194 is OK

🟡 SKIP DOIs

- No DOI given, and none found for title: Bayesian regionalization of urban mobility network...
- No DOI given, and none found for title: Fast nonparametric inference of network backbones ...
- No DOI given, and none found for title: The igraph software package for complex network re...
- No DOI given, and none found for title: Network Science
- No DOI given, and none found for title: Networks
- No DOI given, and none found for title: Clustering of heterogeneous populations of network...
- No DOI given, and none found for title: The physics of higher-order interactions in comple...
- No DOI given, and none found for title: Network motifs: simple building blocks of complex ...

❌ MISSING DOIs

- 10.1103/physreve.109.054306 may be a valid DOI for title: Inference of dynamic hypergraph representations in...
- 10.1038/s42005-023-01270-5 may be a valid DOI for title: Compressing network populations with modal network...
- 10.1038/s42005-022-01029-4 may be a valid DOI for title: Spatial regionalization based on optimal informati...
- 10.1103/physreve.109.034310 may be a valid DOI for title: Identifying hubs in directed networks
- 10.11606/d.45.2021.tde-24022021-164949 may be a valid DOI for title: Community detection in graphs
- 10.1038/s41467-022-34267-9 may be a valid DOI for title: Statistical inference links data and theory in net...
- 10.25080/tcwv9851 may be a valid DOI for title: Exploring network structure, dynamics, and functio...
- 10.1103/physrevx.12.011010 may be a valid DOI for title: Node metadata can produce predictability crossover...

❌ INVALID DOIs

- None

[editorialbot]

👉📄 Download article proof 📄 View article proof on GitHub 📄 👈

[editorialbot]

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⚠️ Note to editors: If these papers look like they might be a good match, click through to the review issue for that paper and invite one or more of the authors before considering asking the reviewers of these papers to review again for JOSS.

[baiyueh]

@editorialbot check references

[editorialbot]

Reference check summary (note 'MISSING' DOIs are suggestions that need verification):

✅ OK DOIs

- 10.1103/physreve.109.054306 is OK
- 10.1038/s42005-023-01270-5 is OK
- 10.1038/s42005-022-01029-4 is OK
- 10.1103/physreve.109.034310 is OK
- 10.1103/physrevresearch.6.033307 is OK
- 10.48550/arXiv.2409.06417 is OK
- 10.6084/m9.figshare.1164194 is OK
- 10.1093/oso/9780198805090.001.0001 is OK
- 10.1016/j.physrep.2009.11.002 is OK
- 10.1038/s41467-022-34267-9 is OK
- 10.1103/physreve.105.014312 is OK
- 10.25080/tcwv9851 is OK
- 10.1038/s41567-021-01371-4 is OK
- 10.1103/physrevx.12.011010 is OK
- 10.1126/science.298.5594.824 is OK

🟡 SKIP DOIs

- No DOI given, and none found for title: The igraph software package for complex network re...
- No DOI given, and none found for title: Network Science

❌ MISSING DOIs

- None

❌ INVALID DOIs

- None

[baiyueh]

@editorialbot generate pdf

[editorialbot]

👉📄 Download article proof 📄 View article proof on GitHub 📄 👈

[editorialbot]

Five most similar historical JOSS papers:

PyDGN: a Python Library for Flexible and Reproducible Research on Deep Learning for Graphs
Submitting author: @diningphil
Handling editor: @arfon (Active)
Reviewers: @idoby, @sepandhaghighi
Similarity score: 0.7292

PyEI: A Python package for ecological inference
Submitting author: @karink520
Handling editor: @drvinceknight (Active)
Reviewers: @matt-graham, @pmyteh
Similarity score: 0.7266

cosasi: Graph Diffusion Source Inference in Python
Submitting author: @lucasmccabe
Handling editor: @danielskatz (Active)
Reviewers: @sara-02, @zoometh
Similarity score: 0.7226

HyperNetX: A Python package for modeling complex network data as hypergraphs
Submitting author: @brendapraggastis
Handling editor: @danielskatz (Active)
Reviewers: @szhorvat, @IvanIsCoding, @drj11
Similarity score: 0.7210

XGI: A Python package for higher-order interaction networks
Submitting author: @nwlandry
Handling editor: @vissarion (Active)
Reviewers: @arashbm, @MridulS
Similarity score: 0.7154

⚠️ Note to editors: If these papers look like they might be a good match, click through to the review issue for that paper and invite one or more of the authors before considering asking the reviewers of these papers to review again for JOSS.

[crvernon]

@editorialbot invite @vissarion as editor

👋 @vissarion can you take this one on as editor?

[editorialbot]

Invitation to edit this submission sent!

[vissarion]

@editorialbot assign me as editor

[editorialbot]

Assigned! @vissarion is now the editor

[vissarion]

Hi @aneeshnaik, @ankurankan, @gchure, @matt-graham, @rafaelorozco would any of you be willing to review this submission for JOSS? We carry out our checklist-driven reviews here in GitHub issues and follow these guidelines: https://joss.readthedocs.io/en/latest/review_criteria.html

[ankurankan]

@vissarion I would be happy to help with the review.

[vissarion]

@editorialbot add @ankurankan as reviewer

[editorialbot]

@ankurankan added to the reviewers list!

[gchure]

Hi @vissarion, happy to review. I'll be able to finish it in ≈3-4 weeks if that timeline is okay.

[abhishektiwari]

@vissarion will not mind being additional reviewer on this network inference paper.

[aneeshnaik]

I would be happy to review also if you're still looking for additional reviewers.

[vissarion]

@editorialbot add @gchure as reviewer

[editorialbot]

@gchure added to the reviewers list!

[vissarion]

@abhishektiwari, @aneeshnaik thank you for your availability!

I will let you know if extra reviewers are needed!

[vissarion]

@editorialbot start review

[editorialbot]

OK, I've started the review over in #7312.